ANNOUNCEMENT

NOBEL PRIZE 2026

This year's laureates, their fields, and the discoveries that earned them the prize.Live nowSee the winners
Moonbase
← Back to Awards
NSFDirectorate for Computer and Information Science and Engineering

Collaborative Research: VINES: Track 1: NSF-RCF: FORMULA3: Optimal Resource Management Using Generalizable AI in Frequency Range 3 Dynamic Programmable Wireless Environments

Active
Institution
Tennessee Technological University, TN
Principal investigator
Muhammad Ismail
Funding
$400K
Duration
2026–2029
Open portfolio

Moonbase score

Still being scored

Abstract

This project studies how future wireless networks can deliver fast, stable, and reliable connections inside buildings and from outdoors to indoors. It focuses on a new range of radio frequencies that can carry much more data than current systems while still covering useful distances. The project explores how smart programmable surfaces placed on walls can redirect wireless signals around obstacles. By combining these smart surfaces with artificial intelligence-based control, the project aims to prevent connection problems before users notice them. At its core, the project advances the science of proactive wireless network control through four tightly integrated technical thrusts. The first thrust develops realistic channel models and datasets using experimental platforms with programmable reflective surfaces operating in the Frequency Range 3 (FR3) upper mid-band. The second thrust designs novel artificial intelligence models that proactively configure beams and reflective surfaces. The third thrust improves model generalization by incorporating environmental context information from integrated sensing and communication, along with continual learning. The fourth thrust provides rigorous evaluation through combined simulation and measurement across dynamic indoor and outdoor-to-indoor scenarios. The project has broad impacts on society, education, and technology development. Reliable and low-latency wireless connectivity supports applications such as augmented reality, virtual reality, remote healthcare, and advanced manufacturing. The project trains graduate students in wireless systems, sensing, and artificial intelligence through hands-on research experiences across participating institutions. This collaborative project brings together investigators from Tennessee Tech University, Texas A&M University, and New York University in the United States, and Aalto University and Tampere University in Finland, to advance next-generation wireless connectivity through an international partnership. Through this international collaboration between the United States and Finland, this project advances the foundation of artificial intelligence native wireless networks that can sense, predict, and adapt to change. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Research team

  • Muhammad IsmailPI
  • Theodore S RappaportCo-PI

LOADING MOONBASE SCORE

Directorate for Computer and Information Science and Engineering01002627DB NSF RESEARCH & RELATED ACTIVITUse-Inspired NextG, GVF - Global Venture Fundwirelessradiostableconnectionsoutdoorproblemshandsbroaderaaltotampere

Questions for Tennessee Technological University

Answered by the team behind this research.

Same researchers, same institution, same topic, scored first.